Urban population growth has been constant for several decades in France. Between 1960 and 2022, it rose from 61.88 percent to 81.51 percent. The phenomenon of urbanization was more significant in the 1960s. Indeed, over this period, the rate of the French population living in cities increased by ten points. The evolution was more weighted over the next 50 years, rising from 71.06 percent in 1970 to 80.98 percent in 2020.An increase in urbanization was accompanied over the same period by a sharp rise in the overall French population, from 55.57 million inhabitants in 1982 to around 68 million in 2024. Paris, an urban giant in France Like in the United Kingdom, the French-style centralized system has led to a high concentration of population around economic, financial, cultural and political centers, all located in the British and French capitals. London and Paris (and its conurbation) are among the largest urban centers on the continent, with Moscow being the most populous. This centralization of power has led to a very heterogenous distribution of population density. The Paris region has a density of more than 1000 inhabitants per km², which is ten times higher than the Haut-de-France region, the second densest region in Metropolitan France.This centralization of power attracts a strong French and foreign workforce. The French capital is by far the most populated city in France. If solely the municipality of Paris is taken into account, it had more than two million inhabitants in 2019, which is more than twice as many as in Marseille and four times as many as in Lyon, the country's second and third most populous cities. Future challenges for French cities Access to employment is no longer the only reason to settle in a town. Other factors come into play in the life choices of city dwellers. In 2019, more than 90% of the French estimated that the presence of green areas was important to settle or not in a district. The pollution level of the city was also considered in the choice of the city. In order to address these pollution problems, municipalities must resolve transportation issues on their own territory. Previously the king of the town, the car is increasingly losing ground to public transport in urban areas. Cities like Paris are relying more on public transport. Between 2011 and 2016, RATP and SNCF have built more than 60 kilometers of tramway tracks . Moreover, the construction of additional train and metro lines in the Grand Paris project aimed at better connecting the suburbs to each other without passing through intramural Paris.Making it easier to travel by bicycle is one of the options chosen by many conurbations to relieve congestion in their cities. Since the early 2000s, self-service bicycles have been a great success in France with more than 2,400 bicycles available in Toulouse or 4,000 in Lyon in 2017. A source of much tension between motorists, municipalities and cyclists, the sharing of the road between 4 and 2 wheelers has, however, been widely developed. In Strasbourg, for example, the municipality had around 1.04 metres of cycle lanes per inhabitant in 2017, the highest rate in France. However, the layout of cycle paths can be perilous and a majority of cyclists in France still feel unsafe on the road.

Prepared by ICPSR under a project to automate major portions of the Statistique Generale de la France, this is a collection of demographic, social, education, economic, population, and vital statistics data for France, 1833-1925. This conversion project is a continuation of one conducted in 1972, for which a similar data collection was created, SOCIAL, DEMOGRAPHIC, AND EDUCATIONAL DATA FOR FRANCE, 1801-1897 (ICPSR 0048). The project to collect and prepare these data was sponsored by two French and two American groups: ICPSR and the Center for Western European Studies at the University of Michigan, and the Fourth and Sixth Sections of the Ecole Pratique des Hautes Etudes and Conseil National de la Recherches Scientifique in France. Both collections include data recorded at the departement, arrondissement, chef-lieu, and ville level. In this collection, materials from the vital statistics series were prepared for selected years rather than for each year in the period from 1900-1925. The years that were chosen clustered around the quinquennial censuses and also included (because of the violent demographic dislocations produced by World War I) each year in the 1914-1919 period. In addition, some vital statistics for the nineteenth century (1836-1850, 1880, and 1892) obtained from fugitive published volumes that could not be located during the course of the 1972 project were prepared. The 136 datasets in this collection contain: (1) French population, economic, and social data obtained from the quenquennial censuses of 1901, 1906, 1911, and 1921, that detail the composition of the population by categories of age, sex, nativity, marital status, religion, place of residence, and occupation, (2) industrial census data for the years 1861-1896, (3) data on primary education in France for 1833, 1901, and 1906, as well as data on secondary and higher education in France for the years 1836-1850, 1880, and 1892, and (4) data from a separate series of annual vital statistics (Mouvement de la Population) that cover the years 1836-1850, 1892, and 1900-1925, citing births, deaths, and marriages in the nation.

About this dataset

Context

The dataset tabulates the population of French Settlement by race. It includes the population of French Settlement across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to understand the population distribution of French Settlement across relevant racial categories.

Key observations

The percent distribution of French Settlement population by race (across all racial categories recognized by the U.S. Census Bureau): 94.80% are white, 0.92% are Black or African American and 4.28% are multiracial.

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2018-2022 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race: This column displays the racial categories (excluding ethnicity) for the French Settlement
• Population: The population of the racial category (excluding ethnicity) in the French Settlement is shown in this column.
• % of Total Population: This column displays the percentage distribution of each race as a proportion of French Settlement total population. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for French Settlement Population by Race & Ethnicity. You can refer the same here

The population density in France is unevenly distributed. The country, which enjoys a great variety of regions and landscapes, is becoming more and more urbanized and big cities concentrate economic activities. Ile-de-France and overseas region: most densely populated French regions In 2020, Ile-de-France was the French region with the highest population density. According to the source, there were 1,021.6 residents per square kilometer in Ile-de-France. In 2023, more than 12.35 million people lived in this region which contains the city of Paris and its greater suburbs. The overseas regions such as Guadeloupe, Reunion, and Martinique, are the most densely populated French regions after the Paris region. On the other hand, Corsica, was the least densely populated region in metropolitan France. However, it is Guyanne, the largest overseas department, which has the lowest density in France with only 3.4 inhabitants per square kilometre. Largely covered by the Amazon jungle, this French territory is almost entirely populated along the coasts. The overall population density in metropolitan France reached 123.27 inhabitants per square kilometer in 2021, compared to 116.91 in 2007. Ile-de-France, and particularly Paris, is the center of most of economic, political, and social activities in France. For instance, the ten most visited national French museums and galleries in 2017 were all located in Paris. In 2014, Ile-de-France was the French region which had the highest expenditure on Research and Development (19 billion euros). Regions in France Hauts-de-France, in the northern part of the country, and Provence-Alpes Côte d’Azur in the southeastern part, were the second and the third most densely populated regions in Metropolitan France. The French southeastern coast is known for being highly urbanized, while its living conditions (sun, Mediterranean sea…) make it one of the most attractive region to work and live in France. Hauts-de-France, which used to be one of the leading industrial regions of the country, now benefits from its geographical proximity to the heart of Europe: Brussels. Furthermore, rural regions like Centre-Val de Loire or Bourgogne Franche-Comté are less populous, and the share of the rural population in France is decreasing for years now.

In 2022, the rural population in France reached 18.49 percent of the total. Although the rate is very high, France has an urbanization rate equivalent to its European neighbors. In 2023, Europe was ranked third continent worldwide in terms of degree of urbanization. 75 percent of the European population was living in cities in 2023, but this figure is expected to decrease by 2050. In France, studies have shown that most of the population lives in urban areas, but many French citizens seemed to aspire to live in the countryside. France: an urban country From 2006 to 2020, the share of French residents living in rural areas kept decreasing, going from roughly 22.6 percent in 2006 to slightly more than 19 percent in 2020. According to Insee, a municipality is rural when it does not reach the threshold of 2,000 inhabitants. In France, more than 13 million individuals were living in the countryside in 2016. In comparison, the urban population amounted to 53 million people that same year and reached more than 80 percent of the total in 2022. The advantages of the countryside A survey conducted by Ifop in 2018 showed that 41 percent of French people wanted to live in a rural town. Despite common beliefs, the countryside appears to have a lot to offer. In addition to a more pleasant living environment, the employment situation seems to be more advantageous in French rural areas. In 2020, the percentage of unemployed people reached 5.5 percent in rural areas, compared to less than nine percent in cities. Similarly, the percentage of labor force participants is higher in rural areas.

Since 2006, France has seen an increase in the population aged 65 and over, while over the same period, the French population aged 59 and under has stagnated or even decreased for the 20-59 age group. While approximately 10 million French people were over 65 in 2006, there were 14.39 million in 2023.

About this dataset

Context

The dataset presents the median household income across different racial categories in French Lick. It portrays the median household income of the head of household across racial categories (excluding ethnicity) as identified by the Census Bureau. The dataset can be utilized to gain insights into economic disparities and trends and explore the variations in median houshold income for diverse racial categories.

Key observations

Based on our analysis of the distribution of French Lick population by race & ethnicity, the population is predominantly White. This particular racial category constitutes the majority, accounting for 80.91% of the total residents in French Lick. Notably, the median household income for White households is $49,722. Interestingly, despite the White population being the most populous, it is worth noting that Black or African American households actually reports the highest median household income, with a median income of $124,643. This reveals that, while Whites may be the most numerous in French Lick, Black or African American households experience greater economic prosperity in terms of median household income.

https://i.neilsberg.com/ch/french-lick-in-median-household-income-by-race.jpeg" alt="French Lick median household income diversity across racial categories">

Content

When available, the data consists of estimates from the U.S. Census Bureau American Community Survey (ACS) 2017-2021 5-Year Estimates.

Racial categories include:

• White
• Black or African American
• American Indian and Alaska Native
• Asian
• Native Hawaiian and Other Pacific Islander
• Some other race
• Two or more races (multiracial)

Variables / Data Columns

• Race of the head of household: This column presents the self-identified race of the household head, encompassing all relevant racial categories (excluding ethnicity) applicable in French Lick.
• Median household income: Median household income, adjusting for inflation, presented in 2022-inflation-adjusted dollars

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for French Lick median household income by race. You can refer the same here

France: Demographic pressures, 0 (low) - 10 (high): The latest value from 2024 is 2.8 index points, a decline from 3.1 index points in 2023. In comparison, the world average is 5.80 index points, based on data from 176 countries. Historically, the average for France from 2007 to 2024 is 3.12 index points. The minimum value, 1.9 index points, was reached in 2020 while the maximum of 4.1 index points was recorded in 2007.

France FR: Birth Rate: Crude: per 1000 People data was reported at 11.700 Ratio in 2016. This records a decrease from the previous number of 12.000 Ratio for 2015. France FR: Birth Rate: Crude: per 1000 People data is updated yearly, averaging 13.800 Ratio from Dec 1960 (Median) to 2016, with 57 observations. The data reached an all-time high of 18.700 Ratio in 1961 and a record low of 11.700 Ratio in 2016. France FR: Birth Rate: Crude: per 1000 People data remains active status in CEIC and is reported by World Bank. The data is categorized under Global Database’s France – Table FR.World Bank.WDI: Population and Urbanization Statistics. Crude birth rate indicates the number of live births occurring during the year, per 1,000 population estimated at midyear. Subtracting the crude death rate from the crude birth rate provides the rate of natural increase, which is equal to the rate of population change in the absence of migration.; ; (1) United Nations Population Division. World Population Prospects: 2017 Revision. (2) Census reports and other statistical publications from national statistical offices, (3) Eurostat: Demographic Statistics, (4) United Nations Statistical Division. Population and Vital Statistics Reprot (various years), (5) U.S. Census Bureau: International Database, and (6) Secretariat of the Pacific Community: Statistics and Demography Programme.; Weighted average;

This statistic shows the total number of male births in France from 2004 to 2022. In 2004, there were 393,477 boys born in France. The number of male births in France peaked in 2010 with more than 410,000 births recorded. The number of boy births has been declining for many years, in 2022 the number dropped below 352,000.

The world's most accurate population datasets. Seven maps/datasets for the distribution of various populations in France: (1) Overall population density (2) Women (3) Men (4) Children (ages 0-5) (5) Youth (ages 15-24) (6) Elderly (ages 60+) (7) Women of reproductive age (ages 15-49).

Context

[INSEE][1] is the official french institute gathering data of many types around France. It can be demographic (Births, Deaths, Population Density...), Economic (Salary, Firms by activity / size...) and more.
It can be a great help to observe and measure inequality in the french population.

Content

Four files are in the dataset :

• base_etablissement_par_tranche_effectif : give information on the number of firms in every french town, categorized by size , come from [INSEE][2].
  • CODGEO : geographique code for the town (can be joined with code_insee column from "name_geographic_information.csv')
  • LIBGEO : name of the town (in french)
  • REG : region number
  • DEP : depatment number
  • E14TST : total number of firms in the town
  • E14TS0ND : number of unknown or null size firms in the town
  • E14TS1 : number of firms with 1 to 5 employees in the town
  • E14TS6 : number of firms with 6 to 9 employees in the town
  • E14TS10 : number of firms with 10 to 19 employees in the town
  • E14TS20 : number of firms with 20 to 49 employees in the town
  • E14TS50 : number of firms with 50 to 99 employees in the town
  • E14TS100 : number of firms with 100 to 199 employees in the town
  • E14TS200 : number of firms with 200 to 499 employees in the town
  • E14TS500 : number of firms with more than 500 employees in the town

• name_geographic_information : give geographic data on french town (mainly latitude and longitude, but also region / department codes and names )

  • EU_circo : name of the European Union Circonscription
  • code_région : code of the region attached to the town
  • nom_région : name of the region attached to the town
  • chef.lieu_région : name the administrative center around the town
  • numéro_département : code of the department attached to the town
  • nom_département : name of the department attached to the town
  • préfecture : name of the local administrative division around the town
  • numéro_circonscription : number of the circumpscription
  • nom_commune : name of the town
  • codes_postaux : post-codes relative to the town
  • code_insee : unique code for the town
  • latitude : GPS latitude
  • longitude : GPS longitude
  • éloignement : i couldn't manage to figure out what was the meaning of this number

• net_salary_per_town_per_category : salaries around french town per job categories, age and sex

  • CODGEO : unique code of the town
  • LIBGEO : name of the town
  • SNHM14 : mean net salary
  • SNHMC14 : mean net salary per hour for executive
  • SNHMP14 : mean net salary per hour for middle manager
  • SNHME14 : mean net salary per hour for employee
  • SNHMO14 : mean net salary per hour for worker
  • SNHMF14 : mean net salary for women
  • SNHMFC14 : mean net salary per hour for feminin executive
  • SNHMFP14 : mean net salary per hour for feminin middle manager
  • SNHMFE14 : mean net salary per hour for feminin employee
  • SNHMFO14 : mean net salary per hour for feminin worker
  • SNHMH14 : mean net salary for man
  • SNHMHC14 : mean net salary per hour for masculin executive
  • SNHMHP14 : mean net salary per hour for masculin middle manager
  • SNHMHE14 : mean net salary per hour for masculin employee
  • SNHMHO14 : mean net salary per hour for masculin worker
  • SNHM1814 : mean net salary per hour for 18-25 years old
  • SNHM2614 : mean net salary per hour for 26-50 years old
  • SNHM5014 : mean net salary per hour for >50 years old
  • SNHMF1814 : mean net salary per hour for women between 18-25 years old
  • SNHMF2614 : mean net salary per hour for women between 26-50 years old
  • SNHMF5014 : mean net salary per hour for women >50 years old
  • SNHMH1814 : mean net salary per hour for men between 18-25 years old
  • SNHMH2614 : mean net salary per hour for men between 26-50 years old
  • SNHMH5014 : mean net salary per hour for men >50 years old

• population : [demographic][3] information in France per town, age, sex and living mode

  • NIVGEO : geographic level (arrondissement, communes...)
  • CODGEO : unique code for the town
  • LIBGEO : name of the town (might contain some utf-8 errors, this information has better quality name_geographic_information)
  • MOCO : cohabitation mode : [list and meaning available in Data description]
  • AGE80_17 : age category (slice of 5 years) | ex : 0 -> people between 0 and 4 years old
  • SEXE : sex, 1 for men | 2 for women
  • NB : Number of people in the category

• departments.geojson : contains the borders of french departments. From [Gregoire David (github)][4]

These datasets can be merged by : CODGEO = code_insee

Acknowledgements

The entire dataset has been created (and actualized) by INSEE, I just uploaded it on Kaggle after doing some jobs and checks ...

This upload contains two Geopackage files of raw data used for urban analysis in the outskirts of Lille and Nice, France. 
The data include building footprints (layer "building"), roads (layer "road"), and administrative boundaries (layer "adm_boundaries")
extracted from version 3.3 of the French dataset BD TOPO®3 (IGN, 2023) for the municipalities of Santes, Hallennes-lez-Haubourdin,
Haubourdin, and Emmerin in northern France (Geopackage "DPC_59.gpkg") and Drap, Cantaron and La Trinité in southern France 
(Geopackage "DPC_06.gpkg").

Metadata for these layers is available here: https://geoservices.ign.fr/sites/default/files/2023-01/DC_BDTOPO_3-3.pdf

Additionally, this upload contains the results of the following algorithms available in GitHub (https://github.com/perezjoan/emc2-WP2?tab=readme-ov-file)

1. The identification of main streets using the QGIS plugin Morpheo (layers "road_morpheo" and "buffer_morpheo") 
https://plugins.qgis.org/plugins/morpheo/ 

2. The identification of main streets in local contexts – connectivity locally weighted (layer "road_LocRelCon")

3. Basic morphometry of buildings (layer "building_morpho")

4. Evaluation of the number of dwellings within inhabited buildings (layer "building_dwellings")

5. Projecting population potential accessible from main streets (layer "road_pop_results")

Project website: http://emc2-dut.org/

Publications using this sample data: 
Perez, J. and Fusco, G., 2024. Potential of the 15-Minute Peripheral City: Identifying Main Streets and Population Within Walking Distance. In: O. Gervasi, B. Murgante, C. Garau, D. Taniar, A.M.A.C. Rocha and M.N. Faginas Lago, eds. Computational Science and Its Applications – ICCSA 2024 Workshops. ICCSA 2024. Lecture Notes in Computer Science, vol 14817. Cham: Springer, pp.50-60. https://doi.org/10.1007/978-3-031-65238-7_4.

Acknowledgement. This work is part of the emc2 project, which received the grant ANR-23-DUTP-0003-01 from the French National Research Agency (ANR) within the DUT Partnership.

This statistic shows the share of the population in France in 2023, by nationality status. It appears that French-born citizens accounted for around 87 percent of the French population, while 8.2 percent of the people living in France in 2023 were foreigners.

In 2024, the female population in France amounted to more than 35 million. Like most of other European countries, France has a female population larger than its male population.

Female population in France

According to the source, the female population in France is increasing since 2004. That year there were more than 32 million women in France, compared to 34.1 million ten years later. Surprisingly, the total number of male births has always been higher than the total number of female births. However, life expectancy in the country is higher for women and the proportion between men and women in France appear to stabilize over time.

Women live longer than men

Studies have shown that the life expectancy at birth was higher than females than for male. In 2023, a baby boy born in France had a life expectancy of 80 years, while it reached 85.7 years for a baby girl. In Europe, as well, as in France, life expectancy gap between men and women is a consistent trend. Health issues and a riskier lifestyle could explain why women outlive men. In 2018, Madrid was the European area where both men and women had the longest life expectancy. It reached 87.8 years for females and 82.2 for males.

PARES Dataset v2 PARES (PArish REcord Survey) contains 535 images of handwritten census tables for years ranging from around 1650 A.D. until 1850 A.D..They come from two French cities, Vic-sur-Seille (French department of Moselle) and Echevronne (French department of Côte d'Or). While they mention very ancient times, the documents are handwritten transcriptions of even older documents and are quite recent, copied from original documents during the 1950's and 1960's for demographic studies led by the INED in France (Institut National des études démographiques − National Institute for Demographic Studies). These copies were made by only a few different writers. The documents are damaged and exhibit different types of degradations. We identified seven different document categories we call C1 to C7. C1 and C3 are generally high-quality documents, without serious damage, consisting of about 90% of the dataset. Other categories include highly damaged documents or documents with specificities. A notable aspect of this dataset is that the records are written using only two different physical paper templates. Categories n°1, 2, 3, 6 and 7 have 25 recordings while the categories 4 and 5 are higher and can record up to 35 recordings. C4 and C5 are the larger templates and differ from the rest of the documents. We published a paper, Text Line Detection in Historical Index Tables: Evaluations on a New French PArish REcord Survey Dataset (PARES), in which we better describe the dataset and the tasks it's possible to run on it.

Historical Dataset of La France Elementary School is provided by PublicSchoolReview and contain statistics on metrics:Total Students Trends Over Years (1987-2023),Total Classroom Teachers Trends Over Years (1987-2023),Distribution of Students By Grade Trends,Student-Teacher Ratio Comparison Over Years (1987-2023),Asian Student Percentage Comparison Over Years (2002-2023),Hispanic Student Percentage Comparison Over Years (1998-2023),Black Student Percentage Comparison Over Years (1991-2023),White Student Percentage Comparison Over Years (1991-2023),Two or More Races Student Percentage Comparison Over Years (2013-2023),Diversity Score Comparison Over Years (1991-2023),Free Lunch Eligibility Comparison Over Years (1993-2023),Reduced-Price Lunch Eligibility Comparison Over Years (1999-2023),Reading and Language Arts Proficiency Comparison Over Years (2011-2022),Math Proficiency Comparison Over Years (2011-2022),Science Proficiency Comparison Over Years (2021-2022),Overall School Rank Trends Over Years (2011-2022)

Abstract

IPUMS-International is an effort to inventory, preserve, harmonize, and disseminate census microdata from around the world. The project has collected the world's largest archive of publicly available census samples. The data are coded and documented consistently across countries and over time to facillitate comparative research. IPUMS-International makes these data available to qualified researchers free of charge through a web dissemination system.

The IPUMS project is a collaboration of the Minnesota Population Center, National Statistical Offices, and international data archives. Major funding is provided by the U.S. National Science Foundation and the Demographic and Behavioral Sciences Branch of the National Institute of Child Health and Human Development. Additional support is provided by the University of Minnesota Office of the Vice President for Research, the Minnesota Population Center, and Sun Microsystems.

Geographic coverage

National coverage

Analysis unit

Dwelling

UNITS IDENTIFIED: - Dwellings: No - Households: Yes - Individuals: Yes - Group quarters: Yes

UNIT DESCRIPTIONS: - Group quarters: A collective household is a group of persons that does not live in an ordinary household, but lives in a collective establishment, sharing meal times.

Universe

Residents of France, of any nationality. Does not include French citizens living in other countries, foreign tourists, or people passing through.

Kind of data

Census/enumeration data [cen]

Sampling procedure

SAMPLE UNIT: Private dwellings and individuals for group quarters and compte a part

SAMPLE FRACTION: 4.2%

SAMPLE UNIVERSE: The microdata sample includes mainland France and Corsica.

SAMPLE SIZE (person records): 2,360,854

Mode of data collection

Face-to-face [f2f]

Research instrument

Separate forms for buildings, group quarters (collective households), group quarters (compte a part), private households, and boats. Four forms for individuals (living in group quarters and private dwellings; two different forms for people compte a part; living in boats).

The urban indicators data available here are analyzed, compiled and published by UN-Habitat’s Global Urban Observatory which supports governments, local authorities and civil society organizations to develop urban indicators, data and statistics. Urban statistics are collected through household surveys and censuses conducted by national statistics authorities. Global Urban Observatory team analyses and compiles urban indicators statistics from surveys and censuses. Additionally, Local urban observatories collect, compile and analyze urban data for national policy development. Population statistics are produced by the United Nations Department of Economic and Social Affairs, World Urbanization Prospects.

This statistic shows the population distribution in France on January 1st, 2024, by age group. In 2024, people aged under 15 accounted for 17 percent of the total French population, whereas around ten percent of the population were 75 years and older. By comparison, the number of members of the population over the age of 65 years has increased even more prominently, reaching 14.14 million in 2023. The number of people living in France has been steadily increasing since 1982, exceeding 68 million in 2024, having thus grown by seven percent during that time.